Senior Ai And Analytics Engineer Jobs

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role The future of analytics isn't dashboards. It's intelligent systems that anticipate questions, surface insights, and help people make better decisions. We're looking for a Senior Analytics Engineer to help build that future at Pearl. In this role, you'll design and develop AI-powered analytics experiences that combine trusted enterprise data with modern AI capabilities, enabling business users to interact with data conversationally and uncover insights faster than ever before. You'll build production AI agents, create scalable semantic data models, develop intelligent analytics applications, and establish best practices for responsible AI across the Analytics organization. Working closely with Product, Engineering, and business leaders, you'll turn emerging AI technologies into real business capabilities that improve decision making across the company. This is an opportunity to help define how AI transforms analytics at Pearl while working on some of the most exciting technologies in data, LLMs, and agentic AI. What You’ll Do Build proactive analytics and AI solutions that surface actionable business insights, anticipate business needs, and enable smarter decision-making. Design and develop AI-powered analytics tools, including conversational interfaces that allow business users to query data using natural language. Build semantic data models and reusab

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Senior AI Security Engineer is responsible for defining, designing, and advancing enterprise-wide security strategies and architectures for AI, GenAI, and machine learning platforms. This role leads the development of secure AI systems at scale by embedding advanced security principles across the AI lifecycle and driving the adoption of standardized, security-by-design practices. The Senior AI Security Engineer partners with engineering, platform, and risk leadership to proactively address emerging AI threats, strengthen organizational security posture, and ensure resilient, compliant, and scalable AI deployments. This role operates with significant autonomy and influences security direction across multiple teams and domains.

You love turning real business problems into working AI solutions — and you’re not afraid to roll up your sleeves to ship them. In this role, you’ll lead Diligent’s internal AI Solutions function , a small, high-impact team that is embedding AI and GenA I into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering. You’ll set the AI vision and roadmap for internal tools, architect solutions, and still build hands-on — from prototypes and reference implementations through to production-grade integrations . You’ll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you’ll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business. If you enjoy being a “player-coach” who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales. Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives. Design and deliver end-to-end AI/GenAI solutions — from ideation and prototyping through production deployment, monitoring, and continuous improvement. Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way. &nbsp

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Our Data and Analytics team is currently looking for a Senior Data Scientist to join us! You’ll be responsible for laying the foundation for a best-in-class business analytics function. You’ll partner closely with our business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as a Senior Data Scientist at Vanta: Build and maintain trusted product data assets using dbt, Snowflake, and modern analytics infrastructure Leverage AI-powered analytics tools and data agents (e.g., Snowflake Cortex) to accelerate insight generation, automate repeatable analysis, and scale decision-making Define and evolve measurement frameworks for product health, customer lifecycle, and AI-powered product experiences Partner closely with Product, Engineering, Design, and Customer Success to influence product strategy through data Help define Vanta’s analytics strategy and AI measurement practices as our product and data platform evolve Lead executive analytics reviews, translating complex analyses into clear recommendations that drive company decisions How to be successful in this role: 4+ years of experience working with data as a Data Scientist, Product Analyst, or Analytics Engineer in an applied business setting Strong foundation in SQL, Python (or R), statistics, and machine learning Experience designing and evaluating experiments, predictive models, and other statistical analyses to inform product decisions Experience building scalable data assets, metrics, and analytical frameworks on modern cloud data platforms (e.g., Snowflake, dbt) Deep experience with da

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: Join our Central Analytics team to build high-quality data marts, tools, and AI-powered workflows that shape player experience and drive game growth. You'll work alongside talented and experienced Analytics Engineers, partnering closely with game and marketing analysts to deliver solutions that make a real difference, all using a modern, cutting-edge technical stack. To truly make an impact, you'll need to learn quickly, thrive in a fast-paced environment, and collaborate closely within the team and with the stakeholders. What You’ll Take On: Write and optimize complex SQL queries to support, experimentation, and model feature engineering across large-scale player datasets. Design, build, and maintain cross-game data marts, providing clean and transformed data ready for Analysts to use.

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brain of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As a NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is looking for an AI Computer Engineer to join its NVIDIA Infrastructure Specialists (NVIS) team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI factory systems in the world! NVIDIA is looking for someone with the ability to work on a dynamic customer-focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyse, define and implement large scale AI Factory projects. The scope of these efforts includes a combination of Networking, System Design and Automation while being the face to the customer. What you will be doing: Primary responsibilities will include deploying, managing, and maintaining AI infrastructure for new and existing customers. Be the domain expert with customers during planning calls through implementation. Handover-related documentation and perform knowledge transfers required to support customers as they begin rolling out some of the most sophisticated systems in the world! Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements. What we need to see: Bachelor’s degree in computer science, Electrical Engineering, or a related field, or equivalent experience.

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Sr. Analytics Engineer, R&D. About the job This position is needed to advance the consistency & quality of our R&D analytics data layer and accelerate the development velocity of analysts. Our Data Science and Analytics team seeks to empower R&D to make data-backed decisions that accelerate innovation and improve product performance. You will work closely within our team and across Product & Engineering to design and maintain a robust analytics data layer that enables trusted reporting on R&D metrics. Responsibilities In this role, you’ll: Design and implement a formal analytics data layer using AWS Glue, Athena / Presto, and LookML Collaborate within the Data Science & Analytics team and across Product & Engineering to define, document, and maintain alignment on metric definition and data lineage Develop and maintain automated data reconciliation and quality checks to

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Staff Software Engineer on the Data Platform team within Platform , you'll define and lead the technical strategy for Coinbase's data infrastructure, spanning ingestion, transformation, warehousing, streaming, and serving systems. This is a foundational role at the intersection of distributed systems, data engineering, and AI-readiness, reporting to the Senior Director of Engineering. You'll set architectural direction, drive multi-quarter roadmaps, and transition the organization from managed-service dependency toward engineering-built, platform-grade infrastructure that powers everything from fraud detection to modern multi-agent AI architectures. What you'll do: Own the technical strategy and architecture for Data Platform, setting direction across data ingestion, transformation, warehousing, streaming, and serving systems while driving engineering-led cost reduction at the infrastructure layer. Architect data infrastructure to natively support AI and ML workloads, ensuring pipelines, data lake systems, and compute can power ML training, feature stores, real-time inference, and multi-agent AI architectures at scale. Drive the evolution to near-real-time data availability, enabling downstream teams across Coinbase to act on fresher data for fraud detection, financial reporting, and analytics. Build alignment and secure commitment from senior leadership

Work Flexibility: Remote As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices. What You Will Do Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation. Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability. Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation. Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models. Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions. Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team. Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity. Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational ef

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE SHOULD YOU ACCEPT THIS CHALLENGE… The GTM BI team at Pure Storage supports Revenue Operations across pipeline, forecasting, seller performance, and executive reporting — and we are at an inflection point. We are midway through a strategic migration to dbt as our transformation standard. Beyond that, our roadmap includes scalable automation frameworks, semantic business intelligence, and AI-enabled workflows that help surface insights with less manual effort. As a Senior Analytics Engineer, you will help drive that journey end-to-end. This role is grounded in modernization first: building scalable dbt foundations, improving quality and engineering standards, and enabling the team to operate more efficiently before scaling broader AI-enabled capabilities. You will partner closely with BI analysts, Sales Operations, Systems teams, and backend engineering partners to modernize how analytics is engineered, governed, and consumed across the organization. This role is for someone who wants to build — not maintain. WHAT YOU’LL DO… Lead and contribute hands-on to the team’s dbt and Snowflake modernization initiatives Build scalable semantic and metrics layers supporting GTM domains including pipeline, forecasting, quota, attainment, and seller performance Design and maintain robust ELT/ETL pipelines, orchestration workflows, and reusable business-facing datasets Build CI/CD, testing, observability, lineage, and data qualit